Pandas Profiling Report

Dataset statistics

Number of variables	40
Number of observations	892
Missing cells	1669
Missing cells (%)	4.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	278.9 KiB
Average record size in memory	320.1 B

Variable types

Categorical	21
Numeric	19

Alerts

`owner` has a high cardinality: 238 distinct values	High cardinality
`farm_name` has a high cardinality: 484 distinct values	High cardinality
`lot_number` has a high cardinality: 167 distinct values	High cardinality
`mill` has a high cardinality: 363 distinct values	High cardinality
`ico_number` has a high cardinality: 531 distinct values	High cardinality
`company` has a high cardinality: 217 distinct values	High cardinality
`altitude` has a high cardinality: 308 distinct values	High cardinality
`region` has a high cardinality: 295 distinct values	High cardinality
`producer` has a high cardinality: 544 distinct values	High cardinality
`grading_date` has a high cardinality: 399 distinct values	High cardinality
`owner1` has a high cardinality: 241 distinct values	High cardinality
`expiration` has a high cardinality: 398 distinct values	High cardinality
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`aroma` is highly correlated with `flavor` and 6 other fields	High correlation
`flavor` is highly correlated with `aroma` and 6 other fields	High correlation
`aftertaste` is highly correlated with `aroma` and 6 other fields	High correlation
`acidity` is highly correlated with `aroma` and 6 other fields	High correlation
`body` is highly correlated with `aroma` and 6 other fields	High correlation
`balance` is highly correlated with `aroma` and 6 other fields	High correlation
`uniformity` is highly correlated with `clean_cup`	High correlation
`clean_cup` is highly correlated with `uniformity`	High correlation
`cupper_points` is highly correlated with `aroma` and 6 other fields	High correlation
`total_cup_points` is highly correlated with `aroma` and 6 other fields	High correlation
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`aroma` is highly correlated with `flavor` and 6 other fields	High correlation
`flavor` is highly correlated with `aroma` and 6 other fields	High correlation
`aftertaste` is highly correlated with `aroma` and 6 other fields	High correlation
`acidity` is highly correlated with `aroma` and 6 other fields	High correlation
`body` is highly correlated with `aroma` and 6 other fields	High correlation
`balance` is highly correlated with `aroma` and 6 other fields	High correlation
`uniformity` is highly correlated with `clean_cup`	High correlation
`clean_cup` is highly correlated with `uniformity`	High correlation
`cupper_points` is highly correlated with `aroma` and 6 other fields	High correlation
`total_cup_points` is highly correlated with `aroma` and 6 other fields	High correlation
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`aroma` is highly correlated with `flavor` and 5 other fields	High correlation
`flavor` is highly correlated with `aroma` and 6 other fields	High correlation
`aftertaste` is highly correlated with `aroma` and 6 other fields	High correlation
`acidity` is highly correlated with `aroma` and 6 other fields	High correlation
`body` is highly correlated with `flavor` and 5 other fields	High correlation
`balance` is highly correlated with `aroma` and 6 other fields	High correlation
`uniformity` is highly correlated with `clean_cup`	High correlation
`clean_cup` is highly correlated with `uniformity`	High correlation
`cupper_points` is highly correlated with `aroma` and 6 other fields	High correlation
`total_cup_points` is highly correlated with `aroma` and 6 other fields	High correlation
`unit_of_measurement` is highly correlated with `in_country_partner` and 1 other fields	High correlation
`in_country_partner` is highly correlated with `unit_of_measurement` and 1 other fields	High correlation
`species` is highly correlated with `countryof_origin`	High correlation
`countryof_origin` is highly correlated with `unit_of_measurement` and 2 other fields	High correlation
`species` is highly correlated with `countryof_origin` and 1 other fields	High correlation
`countryof_origin` is highly correlated with `species` and 18 other fields	High correlation
`numberof_bags` is highly correlated with `countryof_origin` and 3 other fields	High correlation
`bag_weight` is highly correlated with `countryof_origin` and 8 other fields	High correlation
`in_country_partner` is highly correlated with `countryof_origin` and 13 other fields	High correlation
`harvest_year` is highly correlated with `countryof_origin` and 10 other fields	High correlation
`variety` is highly correlated with `countryof_origin` and 4 other fields	High correlation
`processing_method` is highly correlated with `countryof_origin` and 3 other fields	High correlation
`moisture` is highly correlated with `countryof_origin` and 3 other fields	High correlation
`category_one_defects` is highly correlated with `countryof_origin` and 1 other fields	High correlation
`quakers` is highly correlated with `altitude_low_meters` and 2 other fields	High correlation
`color` is highly correlated with `countryof_origin` and 1 other fields	High correlation
`category_two_defects` is highly correlated with `category_one_defects` and 1 other fields	High correlation
`unit_of_measurement` is highly correlated with `countryof_origin` and 2 other fields	High correlation
`altitude_low_meters` is highly correlated with `quakers` and 2 other fields	High correlation
`altitude_high_meters` is highly correlated with `quakers` and 2 other fields	High correlation
`altitude_mean_meters` is highly correlated with `quakers` and 2 other fields	High correlation
`aroma` is highly correlated with `harvest_year` and 7 other fields	High correlation
`flavor` is highly correlated with `countryof_origin` and 8 other fields	High correlation
`aftertaste` is highly correlated with `countryof_origin` and 10 other fields	High correlation
`acidity` is highly correlated with `countryof_origin` and 9 other fields	High correlation
`body` is highly correlated with `countryof_origin` and 8 other fields	High correlation
`balance` is highly correlated with `countryof_origin` and 9 other fields	High correlation
`uniformity` is highly correlated with `aftertaste` and 3 other fields	High correlation
`clean_cup` is highly correlated with `aftertaste` and 4 other fields	High correlation
`sweetness` is highly correlated with `species` and 4 other fields	High correlation
`cupper_points` is highly correlated with `countryof_origin` and 10 other fields	High correlation
`total_cup_points` is highly correlated with `countryof_origin` and 12 other fields	High correlation
`lot_number` has 690 (77.4%) missing values	Missing
`mill` has 109 (12.2%) missing values	Missing
`ico_number` has 108 (12.1%) missing values	Missing
`company` has 131 (14.7%) missing values	Missing
`altitude` has 69 (7.7%) missing values	Missing
`region` has 15 (1.7%) missing values	Missing
`producer` has 20 (2.2%) missing values	Missing
`harvest_year` has 19 (2.1%) missing values	Missing
`variety` has 87 (9.8%) missing values	Missing
`processing_method` has 85 (9.5%) missing values	Missing
`color` has 115 (12.9%) missing values	Missing
`altitude_low_meters` has 69 (7.7%) missing values	Missing
`altitude_high_meters` has 69 (7.7%) missing values	Missing
`altitude_mean_meters` has 69 (7.7%) missing values	Missing
`lot_number` is uniformly distributed	Uniform
`moisture` has 137 (15.4%) zeros	Zeros
`category_one_defects` has 797 (89.3%) zeros	Zeros
`quakers` has 826 (92.6%) zeros	Zeros
`category_two_defects` has 244 (27.4%) zeros	Zeros

Reproduction

Analysis started	2022-02-19 02:10:57.591349
Analysis finished	2022-02-19 02:11:51.573051
Duration	53.98 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

species
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

Arabica	870
Robusta	22

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Arabica
2nd row	Arabica
3rd row	Arabica
4th row	Arabica
5th row	Arabica

Common Values

Value	Count	Frequency (%)
Arabica	870	97.5%
Robusta	22	2.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
arabica	870	97.5%
robusta	22	2.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

owner
Categorical

HIGH CARDINALITY

Distinct	238
Distinct (%)	26.9%
Missing	7
Missing (%)	0.8%
Memory size	7.1 KiB

juan luis alvarado romero	154
ipanema coffees	50
cqi taiwan icp cqi台灣合作夥伴	37
lin, che-hao krude 林哲豪	29
nucoffee	24
Other values (233)	591

Length

Max length	47
Median length	22
Mean length	21.07909605
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	135 ?
Unique (%)	15.3%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	grounds for health admin
4th row	yidnekachew dabessa
5th row	metad plc

Common Values

Value	Count	Frequency (%)
juan luis alvarado romero	154	17.3%
ipanema coffees	50	5.6%
cqi taiwan icp cqi台灣合作夥伴	37	4.1%
lin, che-hao krude 林哲豪	29	3.3%
nucoffee	24	2.7%
the coffee source inc.	21	2.4%
alfredo bojalil	16	1.8%
cadexsa	15	1.7%
bismarck castro	14	1.6%
doi tung development project	13	1.5%
Other values (228)	512	57.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
luis	162	5.7%
juan	159	5.6%
alvarado	154	5.4%
romero	154	5.4%
coffee	65	2.3%
coffees	57	2.0%
de	52	1.8%
ipanema	50	1.8%
cqi	42	1.5%
s.a	40	1.4%
Other values (516)	1894	66.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

countryof_origin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	36
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

Mexico	190
Guatemala	174
Brazil	105
Taiwan	63
Honduras	50
Other values (31)	310

Length

Max length	28
Median length	7
Mean length	8.23206278
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	8 ?
Unique (%)	0.9%

Sample

1st row	Ethiopia
2nd row	Ethiopia
3rd row	Guatemala
4th row	Ethiopia
5th row	Ethiopia

Common Values

Value	Count	Frequency (%)
Mexico	190	21.3%
Guatemala	174	19.5%
Brazil	105	11.8%
Taiwan	63	7.1%
Honduras	50	5.6%
Costa Rica	40	4.5%
Ethiopia	27	3.0%
Tanzania, United Republic Of	27	3.0%
Uganda	23	2.6%
Thailand	20	2.2%
Other values (26)	173	19.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mexico	190	17.7%
guatemala	174	16.2%
brazil	105	9.8%
taiwan	63	5.9%
honduras	50	4.7%
united	48	4.5%
costa	40	3.7%
rica	40	3.7%
ethiopia	27	2.5%
tanzania	27	2.5%
Other values (35)	308	28.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

farm_name
Categorical

HIGH CARDINALITY

Distinct	484
Distinct (%)	54.3%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

various	47
rio verde	23
several	20
finca medina	15
doi tung development project	13
Other values (479)	774

Length

Max length	73
Median length	13
Mean length	15.34641256
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	351 ?
Unique (%)	39.3%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	san marcos barrancas "san cristobal cuch
4th row	yidnekachew dabessa coffee plantation
5th row	metad plc

Common Values

Value	Count	Frequency (%)
various	47	5.3%
rio verde	23	2.6%
several	20	2.2%
finca medina	15	1.7%
doi tung development project	13	1.5%
fazenda capoeirnha	13	1.5%
conquista / morito	11	1.2%
capoeirinha	10	1.1%
los hicaques	10	1.1%
el papaturro	9	1.0%
Other values (474)	721	80.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
el	95	4.4%
finca	79	3.6%
la	77	3.5%
coffee	67	3.1%
various	47	2.2%
fazenda	39	1.8%
	38	1.7%
estate	36	1.7%
santa	35	1.6%
verde	33	1.5%
Other values (747)	1635	75.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

lot_number
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	167
Distinct (%)	82.7%
Missing	690
Missing (%)	77.4%
Memory size	7.1 KiB

1	9
020/17	6
019/17	5
102	3
2016 Tainan Coffee Cupping Event Micro Lot 臺南市咖啡評鑑批次	3
Other values (162)	176

Length

Max length	71
Median length	9
Mean length	10.61386139
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	148 ?
Unique (%)	73.3%

Sample

1st row	102
2nd row	Tsoustructive 2015 Sumatra Typica
3rd row	11/23/0252
4th row	Baby Geisha Washed
5th row	320

Common Values

Value	Count	Frequency (%)
1	9	1.0%
020/17	6	0.7%
019/17	5	0.6%
102	3	0.3%
2016 Tainan Coffee Cupping Event Micro Lot 臺南市咖啡評鑑批次	3	0.3%
11/23/0507	2	0.2%
11/52/1170	2	0.2%
2	2	0.2%
47	2	0.2%
2017南投咖啡評鑑 NANTOU COFFEE EVALUATION EVENT 2017	2	0.2%
Other values (157)	166	18.6%
(Missing)	690	77.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1	10	3.3%
coffee	10	3.3%
	8	2.6%
tainan	6	2.0%
020/17	6	2.0%
evaluation	5	1.7%
019/17	5	1.7%
event	5	1.7%
lot	5	1.7%
2017	5	1.7%
Other values (192)	237	78.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

mill
Categorical

HIGH CARDINALITY
MISSING

Distinct	363
Distinct (%)	46.4%
Missing	109
Missing (%)	12.2%
Memory size	7.1 KiB

beneficio ixchel	90
dry mill	38
ipanema coffees	16
cadexsa	12
beneficio siembras vision (154)	12
Other values (358)	615

Length

Max length	77
Median length	16
Mean length	19.48786718
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	243 ?
Unique (%)	31.0%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	wolensu
4th row	metad plc
5th row	c.p.w.e

Common Values

Value	Count	Frequency (%)
beneficio ixchel	90	10.1%
dry mill	38	4.3%
ipanema coffees	16	1.8%
cadexsa	12	1.3%
beneficio siembras vision (154)	12	1.3%
cigrah s.a de c.v.	11	1.2%
ipanema comercial e exportadora sa	11	1.2%
beneficio exportacafe agua santa	11	1.2%
zaragoza itundujia, oaxaca	11	1.2%
agroindustrias unidas de mexico	8	0.9%
Other values (353)	563	63.1%
(Missing)	109	12.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
beneficio	173	7.4%
ixchel	93	4.0%
de	88	3.8%
coffee	75	3.2%
dry	45	1.9%
mill	45	1.9%
la	36	1.5%
el	35	1.5%
ipanema	27	1.2%
finca	25	1.1%
Other values (673)	1686	72.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ico_number
Categorical

HIGH CARDINALITY
MISSING

Distinct	531
Distinct (%)	67.7%
Missing	108
Missing (%)	12.1%
Memory size	7.1 KiB

0	63
Taiwan	29
2222	9
002/4177/0150	7
002/1660/0105	7
Other values (526)	669

Length

Max length	40
Median length	10
Mean length	8.985969388
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	438 ?
Unique (%)	55.9%

Sample

1st row	2014/2015
2nd row	2014/2015
3rd row	2014/2015
4th row	010/0338
5th row	010/0338

Common Values

Value	Count	Frequency (%)
0	63	7.1%
Taiwan	29	3.3%
2222	9	1.0%
002/4177/0150	7	0.8%
002/1660/0105	7	0.8%
002/1660/0080	6	0.7%
Taiwan台灣	6	0.7%
unknown	5	0.6%
002/1660/0065	5	0.6%
11-951-136	5	0.6%
Other values (521)	642	72.0%
(Missing)	108	12.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	63	7.5%
taiwan	29	3.5%
	11	1.3%
2222	9	1.1%
none	8	1.0%
002/4177/0150	7	0.8%
002/1660/0105	7	0.8%
unspecified	7	0.8%
hdoa	6	0.7%
002/1660/0080	6	0.7%
Other values (548)	682	81.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

company
Categorical

HIGH CARDINALITY
MISSING

Distinct	217
Distinct (%)	28.5%
Missing	131
Missing (%)	14.7%
Memory size	7.1 KiB

unex guatemala, s.a.	86
ipanema coffees	50
blossom valley宸嶧國際	21
nucoffee	20
taiwan coffee laboratory	20
Other values (212)	564

Length

Max length	78
Median length	20
Mean length	20.49671485
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	114 ?
Unique (%)	15.0%

Sample

1st row	metad agricultural developmet plc
2nd row	metad agricultural developmet plc
3rd row	yidnekachew debessa coffee plantation
4th row	metad agricultural developmet plc
5th row	diamond enterprise plc

Common Values

Value	Count	Frequency (%)
unex guatemala, s.a.	86	9.6%
ipanema coffees	50	5.6%
blossom valley宸嶧國際	21	2.4%
nucoffee	20	2.2%
taiwan coffee laboratory	20	2.2%
the coffee source inc.	17	1.9%
ecomtrading	16	1.8%
cadexsa	15	1.7%
siembras vision, s.a.	14	1.6%
宸嶧國際	14	1.6%
Other values (207)	488	54.7%
(Missing)	131	14.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
s.a	200	8.4%
de	141	5.9%
coffee	136	5.7%
guatemala	104	4.4%
unex	86	3.6%
coffees	58	2.4%
ltd	50	2.1%
ipanema	50	2.1%
c.v	37	1.6%
exportadora	36	1.5%
Other values (414)	1476	62.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

altitude
Categorical

HIGH CARDINALITY
MISSING

Distinct	308
Distinct (%)	37.4%
Missing	69
Missing (%)	7.7%
Memory size	7.1 KiB

1100	36
1200	35
4300	31
1400	28
1250	28
Other values (303)	665

Length

Max length	41
Median length	4
Mean length	5.77764277
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	195 ?
Unique (%)	23.7%

Sample

1st row	1950-2200
2nd row	1950-2200
3rd row	1600 - 1800 m
4th row	1800-2200
5th row	1950-2200

Common Values

Value	Count	Frequency (%)
1100	36	4.0%
1200	35	3.9%
4300	31	3.5%
1400	28	3.1%
1250	28	3.1%
1300	27	3.0%
1500	26	2.9%
1700	21	2.4%
1350	17	1.9%
1000	13	1.5%
Other values (298)	561	62.9%
(Missing)	69	7.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1200	50	4.7%
1400	46	4.3%
m	44	4.1%
1300	39	3.6%
1100	38	3.5%
1500	37	3.4%
4300	31	2.9%
1250	29	2.7%
msnm	27	2.5%
4000	26	2.4%
Other values (263)	706	65.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

region
Categorical

HIGH CARDINALITY
MISSING

Distinct	295
Distinct (%)	33.6%
Missing	15
Missing (%)	1.7%
Memory size	7.1 KiB

oriente	79
south of minas	65
veracruz	30
comayagua	16
san marcos	16
Other values (290)	671

Length

Max length	76
Median length	10
Mean length	12.30900798
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	167 ?
Unique (%)	19.0%

Sample

1st row	guji-hambela
2nd row	guji-hambela
3rd row	oromia
4th row	guji-hambela
5th row	oromia

Common Values

Value	Count	Frequency (%)
oriente	79	8.9%
south of minas	65	7.3%
veracruz	30	3.4%
comayagua	16	1.8%
san marcos	16	1.8%
tarrazu	16	1.8%
marcala	15	1.7%
huehuetenango	15	1.7%
antigua	15	1.7%
jinotega	12	1.3%
Other values (285)	598	67.0%
(Missing)	15	1.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
oriente	88	5.4%
minas	84	5.1%
of	70	4.3%
south	69	4.2%
san	36	2.2%
de	35	2.1%
chiapas	32	2.0%
veracruz	31	1.9%
marcos	21	1.3%
la	21	1.3%
Other values (421)	1145	70.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

producer
Categorical

HIGH CARDINALITY
MISSING

Distinct	544
Distinct (%)	62.4%
Missing	20
Missing (%)	2.2%
Memory size	7.1 KiB

Ipanema Agrícola SA	22
VARIOS	12
Ipanema Agricola	12
Ipanema Agricola S.A	11
ROBERTO MONTERROSO	10
Other values (539)	805

Length

Max length	100
Median length	19
Mean length	20.46100917
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	414 ?
Unique (%)	47.5%

Sample

1st row	METAD PLC
2nd row	METAD PLC
3rd row	Yidnekachew Dabessa Coffee Plantation
4th row	METAD PLC
5th row	Bazen Agricultural & Industrial Dev't Plc

Common Values

Value	Count	Frequency (%)
Ipanema Agrícola SA	22	2.5%
VARIOS	12	1.3%
Ipanema Agricola	12	1.3%
Ipanema Agricola S.A	11	1.2%
ROBERTO MONTERROSO	10	1.1%
AMILCAR LAPOLA	9	1.0%
Doi Tung Development Project	9	1.0%
AGROPECUARIA QUIAGRAL	8	0.9%
Reinerio Zepeda	8	0.9%
Martin Gutierrez	7	0.8%
Other values (534)	764	85.7%
(Missing)	20	2.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
de	66	2.4%
ipanema	50	1.8%
coffee	49	1.8%
s.a	48	1.8%
agricola	37	1.4%
	35	1.3%
sa	28	1.0%
ltd	25	0.9%
varios	24	0.9%
jose	23	0.8%
Other values (1031)	2338	85.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

numberof_bags
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	98
Distinct (%)	11.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	151.5560538

Minimum	1
Maximum	1062
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	15
median	150
Q3	275
95-th percentile	320
Maximum	1062
Range	1061
Interquartile range (IQR)	260

Descriptive statistics

Standard deviation	132.1337545
Coefficient of variation (CV)	0.8718474197
Kurtosis	0.9086227062
Mean	151.5560538
Median Absolute Deviation (MAD)	125
Skewness	0.4820286157
Sum	135188
Variance	17459.32907
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
250	148	16.6%
275	123	13.8%
10	84	9.4%
320	58	6.5%
1	58	6.5%
300	50	5.6%
50	33	3.7%
20	30	3.4%
100	26	2.9%
2	21	2.4%
Other values (88)	261	29.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	58	6.5%
2	21	2.4%
3	11	1.2%
4	3	0.3%
5	7	0.8%
6	2	0.2%
7	2	0.2%
8	6	0.7%
10	84	9.4%
11	4	0.4%

Value	Count	Frequency (%)
1062	1	0.1%
550	2	0.2%
500	2	0.2%
450	2	0.2%
440	1	0.1%
400	1	0.1%
380	1	0.1%
377	1	0.1%
360	2	0.2%
320	58	6.5%

bag_weight
Categorical

HIGH CORRELATION

Distinct	42
Distinct (%)	4.7%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

1 kg	265
69 kg	192
60 kg	181
2 kg	99
30 kg	23
Other values (37)	132

Length

Max length	8
Median length	5
Mean length	4.548206278
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13 ?
Unique (%)	1.5%

Sample

1st row	60 kg
2nd row	60 kg
3rd row	1
4th row	60 kg
5th row	60 kg

Common Values

Value	Count	Frequency (%)
1 kg	265	29.7%
69 kg	192	21.5%
60 kg	181	20.3%
2 kg	99	11.1%
30 kg	23	2.6%
50 kg	13	1.5%
6	12	1.3%
70 kg	10	1.1%
20 kg	10	1.1%
10 kg	9	1.0%
Other values (32)	78	8.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kg	845	47.8%
1	275	15.6%
69	192	10.9%
60	181	10.2%
2	101	5.7%
lbs	31	1.8%
30	23	1.3%
6	14	0.8%
50	13	0.7%
5	11	0.6%
Other values (26)	82	4.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

in_country_partner
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	26
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

Specialty Coffee Association	183
AMECAFE	165
Asociacion Nacional Del Café	154
Instituto Hondureño del Café	59
Brazil Specialty Coffee Association	51
Other values (21)	280

Length

Max length	62
Median length	28
Mean length	24.86995516
Min length	7

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.3%

Sample

1st row	METAD Agricultural Development plc
2nd row	METAD Agricultural Development plc
3rd row	Specialty Coffee Association
4th row	METAD Agricultural Development plc
5th row	METAD Agricultural Development plc

Common Values

Value	Count	Frequency (%)
Specialty Coffee Association	183	20.5%
AMECAFE	165	18.5%
Asociacion Nacional Del Café	154	17.3%
Instituto Hondureño del Café	59	6.6%
Brazil Specialty Coffee Association	51	5.7%
Blossom Valley International	46	5.2%
Specialty Coffee Association of Costa Rica	37	4.1%
Africa Fine Coffee Association	33	3.7%
NUCOFFEE	28	3.1%
Uganda Coffee Development Authority	23	2.6%
Other values (16)	113	12.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
coffee	382	13.6%
association	323	11.5%
specialty	286	10.2%
del	220	7.8%
café	220	7.8%
amecafe	165	5.9%
asociacion	154	5.5%
nacional	154	5.5%
instituto	59	2.1%
hondureño	59	2.1%
Other values (46)	786	28.0%

Most occurring characters

Value	Count	Frequency (%)
	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	1	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1	100.0%

harvest_year
Categorical

HIGH CORRELATION
MISSING

Distinct	28
Distinct (%)	3.2%
Missing	19
Missing (%)	2.1%
Memory size	7.1 KiB

2012	233
2014	160
2013	104
2015	98
2016	83
Other values (23)	195

Length

Max length	24
Median length	4
Mean length	4.720504009
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	1.1%

Sample

1st row	2014
2nd row	2014
3rd row	2014
4th row	2014
5th row	March 2010

Common Values

Value	Count	Frequency (%)
2012	233	26.1%
2014	160	17.9%
2013	104	11.7%
2015	98	11.0%
2016	83	9.3%
2017	59	6.6%
2013/2014	25	2.8%
2015/2016	21	2.4%
2011	20	2.2%
2014/2015	15	1.7%
Other values (18)	55	6.2%
(Missing)	19	2.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2012	233	25.2%
2014	160	17.3%
2013	104	11.2%
2015	98	10.6%
2016	86	9.3%
2017	75	8.1%
2013/2014	25	2.7%
2015/2016	21	2.3%
2011	21	2.3%
	18	1.9%
Other values (24)	85	9.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

grading_date
Categorical

HIGH CARDINALITY

Distinct	399
Distinct (%)	44.7%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

July 11th, 2012	22
December 26th, 2013	20
June 6th, 2012	15
July 26th, 2012	13
October 8th, 2015	13
Other values (394)	809

Length

Max length	20
Median length	16
Mean length	16.40246637
Min length	13

Characters and Unicode

Total characters	2
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	226 ?
Unique (%)	25.3%

Sample

1st row	April 4th, 2015
2nd row	April 4th, 2015
3rd row	May 31st, 2010
4th row	March 26th, 2015
5th row	April 4th, 2015

Common Values

Value	Count	Frequency (%)
July 11th, 2012	22	2.5%
December 26th, 2013	20	2.2%
June 6th, 2012	15	1.7%
July 26th, 2012	13	1.5%
October 8th, 2015	13	1.5%
March 29th, 2013	12	1.3%
September 27th, 2012	11	1.2%
October 20th, 2017	11	1.2%
August 16th, 2016	9	1.0%
June 1st, 2017	9	1.0%
Other values (389)	757	84.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2012	218	8.1%
2014	172	6.4%
2015	142	5.3%
june	115	4.3%
2017	109	4.1%
may	104	3.9%
july	103	3.8%
2016	91	3.4%
2013	90	3.4%
april	89	3.3%
Other values (42)	1443	53.9%

Most occurring characters

Value	Count	Frequency (%)
	2	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	2	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	2	100.0%

owner1
Categorical

HIGH CARDINALITY

Distinct	241
Distinct (%)	27.2%
Missing	7
Missing (%)	0.8%
Memory size	7.1 KiB

Juan Luis Alvarado Romero	154
Ipanema Coffees	50
CQI Taiwan ICP CQI台灣合作夥伴	36
Lin, Che-Hao Krude 林哲豪	28
NUCOFFEE	24
Other values (236)	593

Length

Max length	47
Median length	22
Mean length	21.0779661
Min length	3

Characters and Unicode

Total characters	2
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	138 ?
Unique (%)	15.6%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	Grounds for Health Admin
4th row	Yidnekachew Dabessa
5th row	metad plc

Common Values

Value	Count	Frequency (%)
Juan Luis Alvarado Romero	154	17.3%
Ipanema Coffees	50	5.6%
CQI Taiwan ICP CQI台灣合作夥伴	36	4.0%
Lin, Che-Hao Krude 林哲豪	28	3.1%
NUCOFFEE	24	2.7%
The Coffee Source Inc.	21	2.4%
ALFREDO BOJALIL	16	1.8%
CADEXSA	15	1.7%
Bismarck Castro	14	1.6%
Doi Tung Development Project	13	1.5%
Other values (231)	514	57.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
luis	162	5.7%
juan	159	5.6%
alvarado	154	5.4%
romero	154	5.4%
coffee	65	2.3%
coffees	57	2.0%
de	52	1.8%
ipanema	50	1.8%
cqi	42	1.5%
s.a	39	1.4%
Other values (516)	1892	66.9%

Most occurring characters

Value	Count	Frequency (%)
	2	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	2	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	2	100.0%

variety
Categorical

HIGH CORRELATION
MISSING

Distinct	26
Distinct (%)	3.2%
Missing	87
Missing (%)	9.8%
Memory size	7.1 KiB

Bourbon	217
Typica	169
Caturra	124
Other	74
Catuai	70
Other values (21)	151

Length

Max length	21
Median length	7
Mean length	6.850931677
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	0.6%

Sample

1st row	Other
2nd row	Bourbon
3rd row	Other
4th row	Other
5th row	Other

Common Values

Value	Count	Frequency (%)
Bourbon	217	24.3%
Typica	169	18.9%
Caturra	124	13.9%
Other	74	8.3%
Catuai	70	7.8%
Yellow Bourbon	34	3.8%
Mundo Novo	22	2.5%
Catimor	16	1.8%
Pacas	13	1.5%
SL14	13	1.5%
Other values (16)	53	5.9%
(Missing)	87	9.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
bourbon	251	28.9%
typica	169	19.4%
caturra	124	14.3%
other	74	8.5%
catuai	70	8.1%
yellow	34	3.9%
mundo	22	2.5%
novo	22	2.5%
catimor	16	1.8%
pacas	13	1.5%
Other values (20)	74	8.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

processing_method
Categorical

HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	0.6%
Missing	85
Missing (%)	9.5%
Memory size	7.1 KiB

Washed / Wet	579
Natural / Dry	149
Semi-washed / Semi-pulped	44
Other	23
Pulped natural / honey	12

Length

Max length	25
Median length	12
Mean length	12.84262701
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Washed / Wet
2nd row	Washed / Wet
3rd row	Natural / Dry
4th row	Washed / Wet
5th row	Natural / Dry

Common Values

Value	Count	Frequency (%)
Washed / Wet	579	64.9%
Natural / Dry	149	16.7%
Semi-washed / Semi-pulped	44	4.9%
Other	23	2.6%
Pulped natural / honey	12	1.3%
(Missing)	85	9.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	784	32.8%
washed	579	24.3%
wet	579	24.3%
natural	161	6.7%
dry	149	6.2%
semi-washed	44	1.8%
semi-pulped	44	1.8%
other	23	1.0%
pulped	12	0.5%
honey	12	0.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

moisture
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	21
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.09428251121

Minimum	0
Maximum	0.28
Zeros	137
Zeros (%)	15.4%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.1
median	0.11
Q3	0.12
95-th percentile	0.13
Maximum	0.28
Range	0.28
Interquartile range (IQR)	0.02

Descriptive statistics

Standard deviation	0.04462892027
Coefficient of variation (CV)	0.4733531139
Kurtosis	0.8536969419
Mean	0.09428251121
Median Absolute Deviation (MAD)	0.01
Skewness	-1.255459328
Sum	84.1
Variance	0.001991740524
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
0.11	258	28.9%
0.12	208	23.3%
0.1	141	15.8%
0	137	15.4%
0.13	55	6.2%
0.09	22	2.5%
0.14	21	2.4%
0.01	8	0.9%
0.15	7	0.8%
0.08	6	0.7%
Other values (11)	29	3.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	137	15.4%
0.01	8	0.9%
0.02	4	0.4%
0.03	2	0.2%
0.04	2	0.2%
0.05	3	0.3%
0.06	2	0.2%
0.07	4	0.4%
0.08	6	0.7%
0.09	22	2.5%

Value	Count	Frequency (%)
0.28	1	0.1%
0.2	3	0.3%
0.18	1	0.1%
0.17	3	0.3%
0.16	4	0.4%
0.15	7	0.8%
0.14	21	2.4%
0.13	55	6.2%
0.12	208	23.3%
0.11	258	28.9%

category_one_defects
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	13
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3139013453

Minimum	0
Maximum	31
Zeros	797
Zeros (%)	89.3%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	31
Range	31
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.791020006
Coefficient of variation (CV)	5.705678021
Kurtosis	200.5334283
Mean	0.3139013453
Median Absolute Deviation (MAD)	0
Skewness	12.76662765
Sum	280
Variance	3.207752664
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
0	797	89.3%
1	47	5.3%
2	22	2.5%
3	9	1.0%
5	4	0.4%
4	4	0.4%
31	2	0.2%
7	2	0.2%
10	1	0.1%
11	1	0.1%
Other values (3)	3	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	797	89.3%
1	47	5.3%
2	22	2.5%
3	9	1.0%
4	4	0.4%
5	4	0.4%
6	1	0.1%
7	2	0.2%
8	1	0.1%
10	1	0.1%

Value	Count	Frequency (%)
31	2	0.2%
15	1	0.1%
11	1	0.1%
10	1	0.1%
8	1	0.1%
7	2	0.2%
6	1	0.1%
5	4	0.4%
4	4	0.4%
3	9	1.0%

quakers
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1603139013

Minimum	0
Maximum	8
Zeros	826
Zeros (%)	92.6%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7216976433
Coefficient of variation (CV)	4.501778306
Kurtosis	47.68993688
Mean	0.1603139013
Median Absolute Deviation (MAD)	0
Skewness	6.338467266
Sum	143
Variance	0.5208474883
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	826	92.6%
1	29	3.3%
2	24	2.7%
4	3	0.3%
5	3	0.3%
6	3	0.3%
3	2	0.2%
7	1	0.1%
8	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	826	92.6%
1	29	3.3%
2	24	2.7%
3	2	0.2%
4	3	0.3%
5	3	0.3%
6	3	0.3%
7	1	0.1%
8	1	0.1%

Value	Count	Frequency (%)
8	1	0.1%
7	1	0.1%
6	3	0.3%
5	3	0.3%
4	3	0.3%
3	2	0.2%
2	24	2.7%
1	29	3.3%
0	826	92.6%

color
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.5%
Missing	115
Missing (%)	12.9%
Memory size	7.1 KiB

Green	611
Bluish-Green	70
Blue-Green	57
None	39

Length

Max length	12
Median length	5
Mean length	5.947232947
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Green
2nd row	Green
3rd row	Green
4th row	Green
5th row	Green

Common Values

Value	Count	Frequency (%)
Green	611	68.5%
Bluish-Green	70	7.8%
Blue-Green	57	6.4%
None	39	4.4%
(Missing)	115	12.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
green	611	78.6%
bluish-green	70	9.0%
blue-green	57	7.3%
none	39	5.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

category_two_defects
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	30
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.412556054

Minimum	0
Maximum	47
Zeros	244
Zeros (%)	27.4%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	4
95-th percentile	12
Maximum	47
Range	47
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	4.749880898
Coefficient of variation (CV)	1.391883627
Kurtosis	18.41695823
Mean	3.412556054
Median Absolute Deviation (MAD)	2
Skewness	3.461377641
Sum	3044
Variance	22.56136854
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
0	244	27.4%
1	129	14.5%
2	124	13.9%
3	94	10.5%
4	83	9.3%
5	51	5.7%
6	32	3.6%
7	30	3.4%
8	22	2.5%
9	16	1.8%
Other values (20)	67	7.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	244	27.4%
1	129	14.5%
2	124	13.9%
3	94	10.5%
4	83	9.3%
5	51	5.7%
6	32	3.6%
7	30	3.4%
8	22	2.5%
9	16	1.8%

Value	Count	Frequency (%)
47	1	0.1%
38	1	0.1%
34	1	0.1%
32	1	0.1%
30	2	0.2%
28	1	0.1%
26	1	0.1%
23	2	0.2%
22	1	0.1%
21	1	0.1%

expiration
Categorical

HIGH CARDINALITY

Distinct	398
Distinct (%)	44.6%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

July 11th, 2013	22
December 26th, 2014	21
June 6th, 2013	15
July 26th, 2013	13
October 7th, 2016	13
Other values (393)	808

Length

Max length	20
Median length	16
Mean length	16.39461883
Min length	13

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	225 ?
Unique (%)	25.2%

Sample

1st row	April 3rd, 2016
2nd row	April 3rd, 2016
3rd row	May 31st, 2011
4th row	March 25th, 2016
5th row	April 3rd, 2016

Common Values

Value	Count	Frequency (%)
July 11th, 2013	22	2.5%
December 26th, 2014	21	2.4%
June 6th, 2013	15	1.7%
July 26th, 2013	13	1.5%
October 7th, 2016	13	1.5%
March 29th, 2014	12	1.3%
October 20th, 2018	11	1.2%
September 27th, 2013	11	1.2%
September 11th, 2013	9	1.0%
June 17th, 2011	9	1.0%
Other values (388)	756	84.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2013	218	8.1%
2015	172	6.4%
2016	142	5.3%
june	115	4.3%
2018	109	4.1%
may	104	3.9%
july	103	3.8%
2017	91	3.4%
2014	90	3.4%
april	89	3.3%
Other values (42)	1443	53.9%

Most occurring characters

Value	Count	Frequency (%)
	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	1	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1	100.0%

unit_of_measurement
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

m	778
ft	114

Length

Max length	2
Median length	1
Mean length	1.127802691
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	m
2nd row	m
3rd row	m
4th row	m
5th row	m

Common Values

Value	Count	Frequency (%)
m	778	87.2%
ft	114	12.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
m	778	87.2%
ft	114	12.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

altitude_low_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	169
Distinct (%)	20.5%
Missing	69
Missing (%)	7.7%
Infinite	0
Infinite (%)	0.0%
Mean	1871.956144

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	428.148
Q1	1100
median	1300
Q3	1500
95-th percentile	1854.5
Maximum	190164
Range	190163
Interquartile range (IQR)	400

Descriptive statistics

Standard deviation	10058.70195
Coefficient of variation (CV)	5.373364103
Kurtosis	314.2995633
Mean	1871.956144
Median Absolute Deviation (MAD)	200
Skewness	17.5139798
Sum	1540619.906
Variance	101177484.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	67	7.5%
1400	49	5.5%
1500	47	5.3%
1300	43	4.8%
1100	43	4.8%
1250	35	3.9%
1310.64	31	3.5%
1000	29	3.3%
1219.2	28	3.1%
1450	24	2.7%
Other values (159)	427	47.9%
(Missing)	69	7.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	1.2%
12	3	0.3%
13	2	0.2%
40	1	0.1%
100	1	0.1%
125	1	0.1%
150	2	0.2%
157.8864	3	0.3%
160	1	0.1%
168	1	0.1%

Value	Count	Frequency (%)
190164	2	0.2%
110000	1	0.1%
11000	1	0.1%
4287	1	0.1%
4001	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%
3280	3	0.3%

altitude_high_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	165
Distinct (%)	20.0%
Missing	69
Missing (%)	7.7%
Infinite	0
Infinite (%)	0.0%
Mean	1906.597621

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	532.1
Q1	1100
median	1300
Q3	1500
95-th percentile	1900
Maximum	190164
Range	190163
Interquartile range (IQR)	400

Descriptive statistics

Standard deviation	10058.28152
Coefficient of variation (CV)	5.275513513
Kurtosis	314.1102333
Mean	1906.597621
Median Absolute Deviation (MAD)	200
Skewness	17.50592704
Sum	1569129.842
Variance	101169027
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1400	56	6.3%
1200	54	6.1%
1500	43	4.8%
1100	43	4.8%
1300	39	4.4%
1250	37	4.1%
1310.64	31	3.5%
1000	30	3.4%
1700	29	3.3%
1219.2	28	3.1%
Other values (155)	433	48.5%
(Missing)	69	7.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	1.2%
12	3	0.3%
13	2	0.2%
40	1	0.1%
100	1	0.1%
125	1	0.1%
150	2	0.2%
157.8864	3	0.3%
168	1	0.1%
170	1	0.1%

Value	Count	Frequency (%)
190164	2	0.2%
110000	1	0.1%
11000	1	0.1%
5900	1	0.1%
4287	1	0.1%
4001	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%

altitude_mean_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	178
Distinct (%)	21.6%
Missing	69
Missing (%)	7.7%
Infinite	0
Infinite (%)	0.0%
Mean	1889.276883

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	525.7
Q1	1100
median	1300
Q3	1500
95-th percentile	1879.2
Maximum	190164
Range	190163
Interquartile range (IQR)	400

Descriptive statistics

Standard deviation	10058.09841
Coefficient of variation (CV)	5.323782078
Kurtosis	314.2544971
Mean	1889.276883
Median Absolute Deviation (MAD)	200
Skewness	17.51198274
Sum	1554874.874
Variance	101165343.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	56	6.3%
1400	46	5.2%
1300	45	5.0%
1100	41	4.6%
1500	38	4.3%
1250	37	4.1%
1000	31	3.5%
1310.64	31	3.5%
1219.2	28	3.1%
1700	24	2.7%
Other values (168)	446	50.0%
(Missing)	69	7.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	1.2%
12	3	0.3%
13	2	0.2%
40	1	0.1%
100	1	0.1%
125	1	0.1%
150	2	0.2%
157.8864	3	0.3%
168	1	0.1%
170	1	0.1%

Value	Count	Frequency (%)
190164	2	0.2%
110000	1	0.1%
11000	1	0.1%
4287	1	0.1%
4001	1	0.1%
3850	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%

aroma
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.98099118

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	33.33209284
Q1	44.79177209
median	50.88048919
Q3	56.73472462
95-th percentile	65.82315007
Maximum	100
Range	100
Interquartile range (IQR)	11.94295253

Descriptive statistics

Standard deviation	9.766604472
Coefficient of variation (CV)	0.1954063783
Kurtosis	1.118013919
Mean	49.98099118
Median Absolute Deviation (MAD)	6.088717097
Skewness	-0.01152027063
Sum	44583.04413
Variance	95.38656292
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
47.83094141	124	13.9%
53.78866215	108	12.1%
50.88048919	100	11.2%
44.79177209	85	9.5%
56.73472462	79	8.9%
42.16567891	68	7.6%
59.45567646	59	6.6%
39.52621207	57	6.4%
63.7921431	36	4.0%
61.62526178	30	3.4%
Other values (20)	146	16.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
22.67382494	1	0.1%
24.43729959	2	0.2%
26.235936	3	0.3%
27.8607195	4	0.4%
29.57430845	7	0.8%
31.37297135	10	1.1%
33.33209284	18	2.0%
35.36110354	21	2.4%

Value	Count	Frequency (%)
100	1	0.1%
77.32617505	2	0.2%
74.73730615	3	0.3%
72.54104834	5	0.6%
70.69152524	6	0.7%
69.08952549	8	0.9%
67.31179991	14	1.6%
65.82315007	11	1.2%
63.7921431	36	4.0%
61.62526178	30	3.4%

flavor
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	3.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.98010169

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	34.38268431
Q1	43.90740166
median	48.99718117
Q3	57.33580623
95-th percentile	64.46883242
Maximum	100
Range	100
Interquartile range (IQR)	13.42840457

Descriptive statistics

Standard deviation	9.769409756
Coefficient of variation (CV)	0.195465984
Kurtosis	1.104518214
Mean	49.98010169
Median Absolute Deviation (MAD)	5.762348091
Skewness	-0.009760782346
Sum	44582.25071
Variance	95.44136698
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
48.99718117	123	13.8%
52.07203829	103	11.5%
54.75952926	83	9.3%
43.90740166	83	9.3%
57.33580623	72	8.1%
46.28432275	71	8.0%
59.88172946	55	6.2%
41.52614802	50	5.6%
39.57503437	39	4.4%
62.23857099	33	3.7%
Other values (22)	180	20.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
21.80333413	2	0.2%
24.87309706	3	0.3%
28.0479438	9	1.0%
29.7015804	3	0.3%
30.61025345	4	0.4%
31.63104374	7	0.8%
33.20924065	15	1.7%
34.38268431	7	0.8%
36.09338622	31	3.5%

Value	Count	Frequency (%)
100	1	0.1%
76.05831772	4	0.4%
73.764064	2	0.2%
72.54104834	4	0.4%
70.9741794	4	0.4%
69.93656583	4	0.4%
69.18753226	3	0.3%
67.88925965	12	1.3%
66.48857789	10	1.1%
64.46883242	30	3.4%

aftertaste
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	3.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.81679103

Minimum	0
Maximum	100
Zeros	7
Zeros (%)	0.8%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	35.36110354
Q1	43.02108155
median	50.90766055
Q3	56.2087789
95-th percentile	65.32136347
Maximum	100
Range	100
Interquartile range (IQR)	13.18769734

Descriptive statistics

Standard deviation	10.38830436
Coefficient of variation (CV)	0.2085301792
Kurtosis	3.543349748
Mean	49.81679103
Median Absolute Deviation (MAD)	5.439167929
Skewness	-0.6072754651
Sum	44436.5776
Variance	107.9168675
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
48.20403928	109	12.2%
53.57034226	101	11.3%
50.90766055	90	10.1%
45.46849262	82	9.2%
43.02108155	69	7.7%
56.2087789	68	7.6%
58.47385198	56	6.3%
60.79794852	48	5.4%
39.27794048	43	4.8%
63.35271559	38	4.3%
Other values (22)	188	21.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	7	0.8%
26.77086985	1	0.1%
28.22719963	6	0.7%
29.57430845	3	0.3%
30.61025345	6	0.7%
31.37297135	3	0.3%
32.47900721	10	1.1%
33.62786292	8	0.9%
35.36110354	28	3.1%
37.32318827	25	2.8%

Value	Count	Frequency (%)
100	1	0.1%
77.32617505	2	0.2%
74.38451842	4	0.4%
72.98649783	2	0.2%
72.33529267	1	0.1%
71.60080491	3	0.3%
70.17460675	6	0.7%
68.99346225	5	0.6%
67.04502618	20	2.2%
65.32136347	11	1.2%

acidity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	28
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.98701945

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	33.20924065
Q1	43.65732305
median	49.06516085
Q3	57.53645609
95-th percentile	66.25804829
Maximum	100
Range	100
Interquartile range (IQR)	13.87913303

Descriptive statistics

Standard deviation	9.770744375
Coefficient of variation (CV)	0.1954656325
Kurtosis	1.116504553
Mean	49.98701945
Median Absolute Deviation (MAD)	5.663813263
Skewness	-0.004191848072
Sum	44588.42135
Variance	95.46744564
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
49.06516085	115	12.9%
54.72897411	99	11.1%
51.93380027	96	10.8%
46.1674422	91	10.2%
43.65732305	70	7.8%
57.53645609	69	7.7%
41.30451049	58	6.5%
38.70492588	55	6.2%
59.90469214	48	5.4%
61.96975479	32	3.6%
Other values (18)	159	17.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
22.67382494	1	0.1%
24.87309706	3	0.3%
26.51248224	2	0.2%
28.39919509	7	0.8%
30.39908366	8	0.9%
33.20924065	27	3.0%
35.93762439	30	3.4%
38.70492588	55	6.2%

Value	Count	Frequency (%)
100	1	0.1%
79.38635916	1	0.1%
74.73730615	5	0.6%
72.1392805	6	0.7%
70.17460675	6	0.7%
68.89925772	6	0.7%
67.7388212	8	0.9%
66.25804829	16	1.8%
64.06237561	30	3.4%
61.96975479	32	3.6%

body
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.98226537

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	33.62786292
Q1	44.28308103
median	50.31117725
Q3	55.91180053
95-th percentile	65.92884501
Maximum	100
Range	100
Interquartile range (IQR)	11.6287195

Descriptive statistics

Standard deviation	9.760727906
Coefficient of variation (CV)	0.1952838238
Kurtosis	1.119471043
Mean	49.98226537
Median Absolute Deviation (MAD)	6.028096222
Skewness	-0.009035603902
Sum	44584.18071
Variance	95.27180926
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
50.31117725	140	15.7%
44.28308103	100	11.2%
47.14497441	91	10.2%
55.91180053	89	10.0%
53.33947586	78	8.7%
58.69548951	66	7.4%
41.44607853	60	6.7%
38.78541872	55	6.2%
61.45847939	52	5.8%
33.62786292	31	3.5%
Other values (20)	130	14.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
23.36536625	2	0.2%
24.87309706	1	0.1%
25.61548158	1	0.1%
26.51248224	2	0.2%
27.8607195	4	0.4%
29.0258206	3	0.3%
30.61025345	10	1.1%
33.62786292	31	3.5%

Value	Count	Frequency (%)
100	1	0.1%
77.32617505	2	0.2%
75.12690294	2	0.2%
73.22913015	4	0.4%
71.77280037	4	0.4%
70.42569155	4	0.4%
68.45350998	15	1.7%
65.92884501	24	2.7%
63.83008247	22	2.5%
61.45847939	52	5.8%

balance
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	31
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.98188839

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	34.43304051
Q1	43.02108155
median	50.36531914
Q3	55.58829507
95-th percentile	64.68213542
Maximum	100
Range	100
Interquartile range (IQR)	12.56721352

Descriptive statistics

Standard deviation	9.775678817
Coefficient of variation (CV)	0.1955844233
Kurtosis	1.09817778
Mean	49.98188839
Median Absolute Deviation (MAD)	5.232173475
Skewness	-0.01269023919
Sum	44583.84444
Variance	95.56389633
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
50.36531914	132	14.8%
55.58829507	85	9.5%
47.44053644	82	9.2%
45.13314567	77	8.6%
53.21046282	73	8.2%
60.42496563	61	6.8%
40.97361667	57	6.4%
57.96702114	53	5.9%
43.02108155	51	5.7%
36.8912487	38	4.3%
Other values (21)	183	20.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
23.94168228	3	0.3%
25.61548158	1	0.1%
26.235936	2	0.2%
27.45895166	2	0.2%
28.39919509	3	0.3%
29.57430845	5	0.6%
31.95579214	19	2.1%
34.43304051	22	2.5%

Value	Count	Frequency (%)
100	1	0.1%
75.56270041	5	0.6%
73.22913015	2	0.2%
71.77280037	6	0.7%
70.17460675	4	0.4%
69.38974655	3	0.3%
67.96615074	14	1.6%
66.43005638	8	0.9%
64.68213542	27	3.0%
62.80697364	24	2.7%

uniformity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	91.28669015

Minimum	0
Maximum	100
Zeros	2
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	37.093843
Q1	100
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	100
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	22.42395094
Coefficient of variation (CV)	0.245643159
Kurtosis	3.06804578
Mean	91.28669015
Median Absolute Deviation (MAD)	0
Skewness	-2.220169909
Sum	81427.72761
Variance	502.8335759
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
100	774	86.8%
37.093843	74	8.3%
32.88950785	20	2.2%
29.30847476	18	2.0%
23.94168228	3	0.3%
0	2	0.2%
25.61548158	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.2%
23.94168228	3	0.3%
25.61548158	1	0.1%
29.30847476	18	2.0%
32.88950785	20	2.2%
37.093843	74	8.3%
100	774	86.8%

Value	Count	Frequency (%)
100	774	86.8%
37.093843	74	8.3%
32.88950785	20	2.2%
29.30847476	18	2.0%
25.61548158	1	0.1%
23.94168228	3	0.3%
0	2	0.2%

clean_cup
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	94.35743063

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	35.09708327
Q1	100
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	100
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	18.8287358
Coefficient of variation (CV)	0.1995469321
Kurtosis	7.563718217
Mean	94.35743063
Median Absolute Deviation (MAD)	0
Skewness	-3.068448336
Sum	84166.82813
Variance	354.521292
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
100	818	91.7%
35.09708327	39	4.4%
31.10074228	9	1.0%
32.4073974	8	0.9%
28.87741094	6	0.7%
27.01350217	4	0.4%
24.87309706	3	0.3%
29.82539325	2	0.2%
22.67382494	1	0.1%
0	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
22.67382494	1	0.1%
24.87309706	3	0.3%
27.01350217	4	0.4%
28.87741094	6	0.7%
29.82539325	2	0.2%
31.10074228	9	1.0%
32.4073974	8	0.9%
35.09708327	39	4.4%

Value	Count	Frequency (%)
100	818	91.7%
35.09708327	39	4.4%
32.4073974	8	0.9%
31.10074228	9	1.0%
29.82539325	2	0.2%
28.87741094	6	0.7%
27.01350217	4	0.4%
24.87309706	3	0.3%
22.67382494	1	0.1%
20.61364084	1	0.1%

sweetness
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	15
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	94.14493988

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	35.40404857
Q1	100
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	100
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	19.11844474
Coefficient of variation (CV)	0.2030745865
Kurtosis	7.080583488
Mean	94.14493988
Median Absolute Deviation (MAD)	0
Skewness	-2.989670013
Sum	83977.28637
Variance	365.5149293
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
100	815	91.4%
35.40404857	38	4.3%
31.95579214	9	1.0%
33.14677271	6	0.7%
28.0479438	5	0.6%
29.94594953	4	0.4%
25.61548158	3	0.3%
21.80333413	2	0.2%
30.61025345	2	0.2%
31.00653775	2	0.2%
Other values (5)	6	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
21.80333413	2	0.2%
23.94168228	1	0.1%
25.61548158	3	0.3%
26.77086985	1	0.1%
28.0479438	5	0.6%
29.16939688	2	0.2%
29.94594953	4	0.4%
30.61025345	2	0.2%
31.00653775	2	0.2%

Value	Count	Frequency (%)
100	815	91.4%
35.40404857	38	4.3%
33.14677271	6	0.7%
32.68820009	1	0.1%
31.95579214	9	1.0%
31.00653775	2	0.2%
30.61025345	2	0.2%
29.94594953	4	0.4%
29.16939688	2	0.2%
28.0479438	5	0.6%

cupper_points
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	37
Distinct (%)	4.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.01266618

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	33.90891031
Q1	43.3514376
median	50.44655424
Q3	57.01416981
95-th percentile	66.54771646
Maximum	100
Range	100
Interquartile range (IQR)	13.66273221

Descriptive statistics

Standard deviation	9.89330587
Coefficient of variation (CV)	0.1978160059
Kurtosis	1.605191849
Mean	50.01266618
Median Absolute Deviation (MAD)	6.567615576
Skewness	0.1069872293
Sum	44611.29823
Variance	97.87750103
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=37)

Value	Count	Frequency (%)
50.44655424	105	11.8%
45.75372559	85	9.5%
52.99670568	81	9.1%
48.02477156	73	8.2%
43.3514376	66	7.4%
55.14568257	64	7.2%
58.94266814	53	5.9%
57.01416981	48	5.4%
41.2841325	45	5.0%
38.23303306	40	4.5%
Other values (27)	232	26.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
23.94168228	3	0.3%
25.61548158	1	0.1%
26.77086985	3	0.3%
28.39919509	5	0.6%
29.82539325	5	0.6%
30.61025345	3	0.3%
32.2611788	15	1.7%
33.90891031	11	1.2%

Value	Count	Frequency (%)
100	2	0.2%
77.32617505	1	0.1%
76.05831772	1	0.1%
75.12690294	1	0.1%
73.764064	2	0.2%
72.1392805	6	0.7%
70.17460675	6	0.7%
68.99346225	5	0.6%
68.20398738	4	0.4%
67.7388212	3	0.3%

total_cup_points
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	157
Distinct (%)	17.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.99488243

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	34.17684993
Q1	43.40287947
median	50
Q3	56.63139403
95-th percentile	65.80954703
Maximum	100
Range	100
Interquartile range (IQR)	13.22851456

Descriptive statistics

Standard deviation	9.830634988
Coefficient of variation (CV)	0.1966328254
Kurtosis	1.090328273
Mean	49.99488243
Median Absolute Deviation (MAD)	6.597120531
Skewness	-0.001134807223
Sum	44595.43513
Variance	96.64138426
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
54.8361287	25	2.8%
50	22	2.5%
50.59557225	22	2.5%
53.89120998	22	2.5%
45.79841648	21	2.4%
47.55248356	21	2.4%
46.76091832	19	2.1%
52.36377406	19	2.1%
51.83727257	19	2.1%
53.29640585	18	2.0%
Other values (147)	684	76.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
20.61364084	1	0.1%
22.67382494	1	0.1%
23.94168228	1	0.1%
25.26269385	2	0.2%
26.235936	1	0.1%
26.77086985	1	0.1%
27.24232834	1	0.1%
27.66470733	1	0.1%
28.0479438	1	0.1%

Value	Count	Frequency (%)
100	1	0.1%
79.38635916	1	0.1%
77.32617505	1	0.1%
76.05831772	1	0.1%
75.12690294	1	0.1%
74.38451842	1	0.1%
73.764064	1	0.1%
73.22913015	1	0.1%
72.75767166	1	0.1%
71.9520562	3	0.3%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	species	owner	countryof_origin	farm_name	lot_number	mill	ico_number	company	altitude	region	producer	numberof_bags	bag_weight	in_country_partner	harvest_year	grading_date	owner1	variety	processing_method	moisture	color	category_two_defects	expiration	unit_of_measurement	altitude_low_meters	altitude_high_meters	altitude_mean_meters	aroma	flavor	aftertaste	acidity	body	balance	uniformity	clean_cup	sweetness	cupper_points	total_cup_points
0	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	NaN	Washed / Wet	0.12	Green	0	April 3rd, 2016	m	1950.0	2200.0	2075.0	77.326175	100.000000	100.000000	100.000000	77.326175	71.772800	100.000000	100.0	100.000000	75.126903	100.000000
1	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	Other	Washed / Wet	0.12	Green	1	April 3rd, 2016	m	1950.0	2200.0	2075.0	100.000000	76.058318	74.384518	79.386359	75.126903	71.772800	100.000000	100.0	100.000000	72.139280	79.386359
2	Arabica	grounds for health admin	Guatemala	san marcos barrancas "san cristobal cuch	NaN	NaN	NaN	NaN	1600 - 1800 m	NaN	NaN	5	1	Specialty Coffee Association	NaN	May 31st, 2010	Grounds for Health Admin	Bourbon	NaN	0.00	NaN	0	May 31st, 2011	m	1600.0	1800.0	1700.0	72.541048	72.541048	72.986498	72.139280	73.229130	71.772800	100.000000	100.0	100.000000	77.326175	77.326175
3	Arabica	yidnekachew dabessa	Ethiopia	yidnekachew dabessa coffee plantation	NaN	wolensu	NaN	yidnekachew debessa coffee plantation	1800-2200	oromia	Yidnekachew Dabessa Coffee Plantation	320	60 kg	METAD Agricultural Development plc	2014	March 26th, 2015	Yidnekachew Dabessa	NaN	Natural / Dry	0.11	Green	2	March 25th, 2016	m	1800.0	2200.0	2000.0	67.311800	73.764064	72.986498	72.139280	77.326175	69.389747	100.000000	100.0	100.000000	73.764064	76.058318
4	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	Other	Washed / Wet	0.12	Green	2	April 3rd, 2016	m	1950.0	2200.0	2075.0	69.089525	72.541048	71.600805	74.737306	75.126903	70.174607	100.000000	100.0	100.000000	72.139280	75.126903
5	Arabica	ethiopia commodity exchange	Ethiopia	aolme	NaN	c.p.w.e	010/0338	NaN	1570-1700	oromia	Bazen Agricultural & Industrial Dev't Plc	300	60 kg	Ethiopia Commodity Exchange	March 2010	September 2nd, 2010	Ethiopia Commodity Exchange	NaN	NaN	0.03	NaN	0	September 2nd, 2011	m	1570.0	1700.0	1635.0	69.089525	69.936566	74.384518	72.139280	73.229130	73.229130	100.000000	100.0	35.404049	76.058318	74.384518
6	Arabica	ethiopia commodity exchange	Ethiopia	aolme	NaN	c.p.w.e	010/0338	NaN	1570-1700	oromiya	Bazen Agricultural & Industrial Dev't Plc	300	60 kg	Ethiopia Commodity Exchange	March 2010	September 2nd, 2010	Ethiopia Commodity Exchange	NaN	NaN	0.03	NaN	0	September 2nd, 2011	m	1570.0	1700.0	1635.0	77.326175	76.058318	77.326175	72.139280	73.229130	71.772800	37.093843	100.0	35.404049	73.764064	73.764064
7	Arabica	diamond enterprise plc	Ethiopia	tulla coffee farm	NaN	tulla coffee farm	2014/15	diamond enterprise plc	1795-1850	snnp/kaffa zone,gimbowereda	Diamond Enterprise Plc	50	60 kg	METAD Agricultural Development plc	2014	March 30th, 2015	Diamond Enterprise Plc	Other	Natural / Dry	0.10	Green	4	March 29th, 2016	m	1795.0	1850.0	1822.5	65.823150	73.764064	74.384518	74.737306	55.911801	71.772800	100.000000	100.0	100.000000	70.174607	73.229130
8	Arabica	mohammed lalo	Ethiopia	fahem coffee plantation	NaN	NaN	NaN	fahem coffee plantation	1855-1955	oromia	Fahem Coffee Plantation	300	60 kg	METAD Agricultural Development plc	2014	March 27th, 2015	Mohammed Lalo	NaN	Natural / Dry	0.10	NaN	1	March 26th, 2016	m	1855.0	1955.0	1905.0	67.311800	76.058318	71.600805	74.737306	58.695490	67.966151	100.000000	100.0	100.000000	72.139280	72.757672
9	Arabica	cqi q coffee sample representative	United States	el filo	NaN	NaN	unknown	coffee quality institute	meters above sea level: 1.872	antioquia	Alfredo De Jesús López Pérez	10	1 kg	Almacafé	2014	March 13th, 2015	CQI Q Coffee Sample Representative	Other	Washed / Wet	0.00	NaN	0	March 12th, 2016	m	1872.0	1872.0	1872.0	69.089525	70.974179	70.174607	70.174607	68.453510	67.966151	100.000000	100.0	100.000000	70.174607	71.952056

Last rows

	species	owner	countryof_origin	farm_name	lot_number	mill	ico_number	company	altitude	region	producer	numberof_bags	bag_weight	in_country_partner	harvest_year	grading_date	owner1	variety	processing_method	moisture	color	category_two_defects	expiration	unit_of_measurement	altitude_low_meters	altitude_high_meters	altitude_mean_meters	aroma	flavor	aftertaste	acidity	body	balance	uniformity	clean_cup	sweetness	cupper_points	total_cup_points
882	Robusta	andrew hetzel	India	sethuraman estate	NaN	NaN	0000	sethuraman estate	1000m	chikmagalur	Nishant Gurger	300	1 kg	Specialty Coffee Association	2015	April 30th, 2015	Andrew Hetzel	NaN	NaN	0.00	Green	0	April 29th, 2016	m	1000.0	1000.0	1000.0	56.734725	57.335806	58.473852	54.728974	53.339476	53.210463	100.000000	100.000000	28.047944	58.942668	45.301533
883	Robusta	andrew hetzel	India	sethuraman estates	NaN	sethuraman estates	NaN	cafemakers, llc	750m	chikmagalur	Nishant Gurjer	140	2 kg	Specialty Coffee Association	2013	June 3rd, 2013	Andrew Hetzel	NaN	Natural / Dry	0.13	Blue-Green	0	June 3rd, 2014	m	750.0	750.0	750.0	47.830941	48.997181	45.468493	59.904692	55.911801	60.424966	100.000000	100.000000	30.610253	58.942668	44.681783
884	Robusta	kawacom uganda ltd	Uganda	bushenyi	NaN	kawacom	0	kawacom uganda ltd	1600	western	Kawacom uganda ltd	1	60 kg	Uganda Coffee Development Authority	2013	June 27th, 2014	Kawacom Uganda LTD	NaN	NaN	0.12	Green	1	June 27th, 2015	m	1600.0	1600.0	1600.0	42.165679	52.072038	53.570342	57.536456	58.695490	55.588295	100.000000	100.000000	29.945950	52.996706	43.402879
885	Robusta	mannya coffee project	Uganda	mannya coffee project	NaN	mannya coffee project	0	mannya coffee project	1200	southern	Mannya coffee project	6	60 kg	Uganda Coffee Development Authority	2013	June 27th, 2014	Mannya coffee project	NaN	NaN	0.12	Green	1	June 27th, 2015	m	1200.0	1200.0	1200.0	56.734725	46.284323	48.204039	51.933800	55.911801	53.210463	100.000000	100.000000	29.169397	50.446554	41.918017
886	Robusta	andrew hetzel	India	sethuraman estates	NaN	NaN	NaN	cafemakers	750m	chikmagalur	Nishant Gurjer	100	2 kg	Specialty Coffee Association	2014	May 19th, 2014	Andrew Hetzel	NaN	NaN	0.00	Bluish-Green	1	May 19th, 2015	m	750.0	750.0	750.0	53.788662	54.759529	53.570342	43.657323	53.339476	50.365319	100.000000	100.000000	25.615482	50.446554	40.846745
887	Robusta	andrew hetzel	India	sethuraman estates	NaN	sethuraman estates	NaN	cafemakers, llc	750m	chikmagalur	Nishant Gurjer	250	2 kg	Specialty Coffee Association	2013	June 20th, 2013	Andrew Hetzel	NaN	Natural / Dry	0.00	Green	0	June 20th, 2014	m	750.0	750.0	750.0	50.880489	46.284323	50.907661	59.904692	47.144974	50.365319	100.000000	100.000000	25.615482	52.996706	40.846745
888	Robusta	andrew hetzel	United States	sethuraman estates	NaN	sethuraman estates	NaN	cafemakers, llc	3000'	chikmagalur	Sethuraman Estates	100	1 kg	Specialty Coffee Association	2012	February 29th, 2012	Andrew Hetzel	Arusha	Natural / Dry	0.00	Green	0	February 28th, 2013	m	3000.0	3000.0	3000.0	61.625262	48.997181	50.907661	46.167442	47.144974	47.440536	37.093843	100.000000	28.047944	45.753726	38.318360
889	Robusta	luis robles	Ecuador	robustasa	Lavado 1	our own lab	NaN	robustasa	NaN	san juan, playas	Café Robusta del Ecuador S.A.	1	2 kg	Specialty Coffee Association	2016	January 19th, 2016	Luis Robles	NaN	NaN	0.00	Blue-Green	1	January 18th, 2017	m	NaN	NaN	NaN	56.734725	52.072038	48.204039	51.933800	0.000000	60.424966	100.000000	100.000000	29.945950	58.942668	36.787733
890	Robusta	luis robles	Ecuador	robustasa	Lavado 3	own laboratory	NaN	robustasa	40	san juan, playas	Café Robusta del Ecuador S.A.	1	2 kg	Specialty Coffee Association	2016	January 19th, 2016	Luis Robles	NaN	NaN	0.00	Blue-Green	0	January 18th, 2017	m	40.0	40.0	40.0	47.830941	54.759529	60.797949	57.536456	20.613641	0.000000	100.000000	100.000000	32.688200	72.139280	35.186334
891	Robusta	james moore	United States	fazenda cazengo	NaN	cafe cazengo	NaN	global opportunity fund	795 meters	kwanza norte province, angola	Cafe Cazengo	1	1 kg	Specialty Coffee Association	2014	December 23rd, 2014	James Moore	NaN	Natural / Dry	0.00	NaN	6	December 23rd, 2015	m	795.0	795.0	795.0	42.165679	43.907402	43.021082	46.167442	50.311177	40.973617	37.093843	35.097083	25.615482	41.284132	33.271008

Overview

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Pie chart

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Common Values

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Most occurring characters

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Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category